Generative AI Data Scientist & ML Engineer

RBC; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

RBC in Toronto is seeking a Data Scientist / Researcher specializing in Generative AI to develop and optimize large language models for enterprise applications. You will fine-tune models, create advanced vector search systems, and build autonomous AI agents that support customer service, data analysis, and decision making.

You will collaborate with other data scientists and ML engineers, validate models with rigorous benchmarks, and deploy solutions into production while documenting

Qualifications

• PhD or master's in Engineering/CS/Data Science or related field.
• 8+ years of research in ML applications with a focus on engineering/computer science.
• Proficient in Python and ML libraries (NumPy, Pandas, Matplotlib, OpenCV, Scikit-Learn, TensorFlow, Keras, PyTorch, PySpark).
• Strong knowledge of ML techniques (supervised/unsupervised, transformers, CNNs, RNNs, GANs).
• Experience with large datasets (TBs) and efficient models; ETL/data cleaning.
• Familiarity with Git-based workflows and cloud platforms (Databricks, Azure/AWS).
• Excellent communication and ability to lead cross-functional teams.

Responsibilities

• Fine-Tune and optimize LLMs for corporate applications.
• Develop advanced vector search and indexing techniques.
• Design and build autonomous AI agents for complex tasks.
• Preprocess data, perform feature extraction/engineering.
• Evaluate models and tune hyperparameters; conduct benchmarks.
• Research novel algorithms to improve efficiency and scalability.
• Deploy LLMs and AI agents into production; integrate with systems.
• Monitor production models and implement improvements.
• Collaborate with data scientists, ML engineers, and domain experts.
• Document methodologies and share findings through presentations/reports.

Skills

Python

NumPy

Pandas

TensorFlow

Keras

PyTorch

Scikit-Learn

SQL

C++

MATLAB

R

PySpark

NLP

Education

PhD or Master’s degree in Engineering/CS/Data Science

Tools

GitLab

GitHub

Bitbucket

JIRA

VSCode

Jupyter Notebook

Spyder

Eclipse

Databricks

Azure Databricks

AWS S3

Job description

What is the opportunity?

Are you passionate about pushing the boundaries of artificial intelligence? Do you thrive in environments where innovation and cutting-edge research are at the forefront? We are offering an exciting opportunity to join our team as a Data Scientist / Researcher specializing in Generative AI Models. In this role, you will develop and optimise and use Large Language Models (LLM's), to solve complex problems and drive innovation in our AI solutions.

Job Description

As a researcher in this role, you will focus on the technical implementation and optimization of large language models (LLMs) to bring autonomous AI agents to life within a corporate setting. Your responsibilities will include:

• Fine-Tune LLMs: Customize and optimize pre-trained LLMs for specific corporate applications, ensuring high performance and accuracy in various NLP tasks such as text classification, summarization, and entity recognition.
• Vector Search Methodology: Develop and implement advanced vector search techniques, including the creation of efficient indexing and retrieval systems, to enhance the organization's ability to quickly and accurately access relevant information.
• Autonomous AI Agents: Design and build autonomous AI agents capable of performing complex tasks autonomously, such as customer service automation, data analysis, and decision‑making support.
• Data Preprocessing and Feature Engineering: Prepare and preprocess large datasets, perform feature extraction and engineering, and ensure data quality for training and validating models.
• Model Evaluation and Tuning: Conduct thorough evaluations of model performance using appropriate metrics and benchmarks. Perform hyperparameter tuning to optimize model configurations.
• Algorithm Development: Research and implement novel algorithms and techniques to improve model efficiency, scalability, and robustness.
• Deployment and Integration: Work on deploying LLMs and AI agents into production environments, ensuring seamless integration with existing systems and workflows.
• Continuous Improvement: Monitor model performance in production, diagnose issues, and implement improvements and updates as needed to maintain and enhance model effectiveness.
• Collaborative Research: Collaborate with other data scientists, machine learning engineers, and domain experts to identify new opportunities for applying LLMs and AI agents, and contribute to joint research projects.
• Documentation and Knowledge Sharing: Document your methodologies, experiments, and findings comprehensively, and share knowledge with the team through presentations, reports, and technical discussions.

What do you need to succeed?

Must-Have:

• Educational Background
  • PhD or Master's degree in Engineering, Computer Science, Data Science, or a related field.
• Research Experience
  • 8+ years of research experience in Engineering, Computer Science or related fields with a focus on machine learning applications.
  • Proven ability to handle and analyze large datasets (over terabytes of data) and deliver efficient models promptly.
• Technical Skills
  • Proficient in Python and libraries such as NumPy, Pandas, Matplotlib, OpenCV, Scikit-Learn, TensorFlow, Keras, PyTorch, and PySpark.
  • Skilled in C++, MATLAB, SQL (MySQL), and R.
  • Strong understanding of machine learning techniques, including supervised and unsupervised learning, classification, decision trees, deep neural networks, CNNs, RNNs, AutoEncoders, GANs, and Transformers.
  • Experience with regression modeling, time series analysis, data mining, data cleaning, and ETL processes.
• Tools and Platforms
  • Familiarity with GitLab, GitHub, Bitbucket, JIRA, VSCode, Jupyter Notebook, Spyder, and Eclipse.
  • Experience with cloud platforms and tools such as Databricks, Azure Databricks, and AWS S3.
• Analytical and Problem‑Solving Skills
  • Exceptional analytical abilities with a talent for identifying model weaknesses and optimizing performance.
  • Strong initiative in approaching complex problems with innovative solutions.
• Interpersonal Skills
  • Excellent communication skills with the ability to lead and collaborate within cross‑functional teams.
  • Proven organizational skills with the ability to manage multiple large‑scale projects simultaneously.

Nice to Have:

• Experience in developing machine learning algorithms for video recognition and computer vision applications.
• Background in high‑energy physics research and familiarity with international laboratory environments like CERN or similar.
• Published research in reputable journals and contributions to significant projects in the AI and physics communities.
• Recognition through awards or scholarships in related fields.

What's in it for you?

• Work on groundbreaking AI projects that have a significant impact on the industry.
• Be part of a forward‑thinking team that values creativity and innovation.
• Opportunities for continuous learning through training, workshops, and conferences.
• Mentorship programs and career development plans to help you reach your goals.
• Attractive salary and benefits package that rewards your expertise and contributions.
• Performance bonuses and recognition programs.

Job Skills

Artificial Intelligence (AI), Big Data Management, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language), Statistical Analysis

Additional Job Details

Address: RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: PERSONAL & COMMERCIAL BANKING

Job Type: Regular

Pay Type: Salaried

Posted Date: 2026-09-09

Application Deadline: 2026-10-31

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

Note

Applications will be accepted until 11:59 PM on the day prior to the application deadline date above